Results of the iSEGMound Workflow
In this Master’s thesis two data preparation methods (using a plain DTM vs. a Multi-Scale Topographic Index, as described an explained in Chapter 4) and two segmentation methods (Watershed and Region Growing, as described in Chapter 2 and explained in Chapter 4) were examined, applied and compared, resulting in four workflows. The basic settings and the exact structure and process for the four workflows were tested and debugged on the Train DTM (one 1x1 km tile) and then applied and to the Train Area (five 1x1 km tile) to understand the relationship between the size of the area of investigation and the variable settings of the respective algorithms. These settings were the adjusted and the most effective workflow was chosen (based on the Train Area). This was followed by the application of the selected workflow to the five Areas of Interests: AoI 1, AoI 2, AoI 3, AoI 4 and AoI 5.
First let’s have inspect the chosen morphometric derivative, the Multi-Scale Topographic Index (later MSTPI), on the example of the Train DTM:
Multi-Scale Topographic Index of the Train DTM, Scale 1:4450.
As a reminder let’s see where the burial mound groups Site ID 5 (black) and Site ID 35 (blue) are located in the Training DTM:
Multi-Scale Topographic Index of the Train DTM with bruial mound groups Site ID 5 and 35. Scale 1:4450.
We know from Dobiat et al. 1994, that Site ID 35 was identified as two mounds. As in Chapter 4 discussed, the mounds visible in Figure 68 were possible to be identified on ground.
Results of the Training DTM
The workflows applied on the Training DTM are the following: 5a_iSEG05_WS, 5b_iSEG05_mtpi_WS, 5c_iSEG05_RG, and 5d_iSEG05_mtpi_RG.
Let’s plot the results of the Training DTM by segmentation. Left the Watershed Segmentation based on a DTM (iSEG05_WS, orange segments) and on the SAGA MTPI (iSEG05_mtpi_WS, lilac segments). Right the Region Growing Segmentation based on a DTM (iSEG05_RG, light blue) and on the SAGA MTPI (iSEG05_mtpi_RG, brown):
iSEG WS in orange and iSEG mtpi WS in lilac nect to iSEG RG in light blue and iSEG mtpi RG in brown, Scale 1:4450.
The first thing that catches the eyes is that both segmentation methods were able to detect Site ID 35, using the SAGA MTPI. Thus it is already clear from this early step on, that in the case of these scarcely preserved burial mounds it is useful to work with morphometric derivatives. When comparing the two segmentation methods, it is apparent, that Watershed segmentation produces more segments than Region Growing.
Results of the Training Area
Before discussing the results of the segmentations, first let’s inspect Site ID 7 and Site ID 14.
Site ID 7 is situated relatively near to the North of Site IDs 5 and 35. The group is constituted of 9 burials, roughly in an elongated line, counted from Southwest to Northeast. When inspecting the mounds, it can be seen that, similar to Site ID 5-9, these are also very near to the forestry commuting routes. Also they already show erosion (mound Site ID 7-5 to 9), mainly in road proximity. This situation has already worsened since 2009/2010, the collection date of the LiDAR data. This burial mound group is similarly preserved such as the average height of the mounds of Site ID 5.
Site ID 14 stretches a little further away to the South and consists of altogether 18 burials. This burial mound group spreads similarly elongated as Site ID 7, although a grouping can be made out in the center region of the group. What is striking about this group is, that many of the mounds - apart from mound 8, which is cut right at the middle - have been just missed or only slightly touched by service roads. The situation of burial mound Site ID 14-8 already indicated, that it is going to be hard to detect this mound properly, because it might be will be difficult to distinguish from the road which is cutting it.
